Dehydroascorbate induces plant resistance in rice against root‐knot nematode Meloidogyne graminicola

Abstract Ascorbic acid (AsA) is an important antioxidant in plants and regulates various physiological processes. In this study, we show that exogenous treatments with the oxidized form of AsA, that is, dehydroascorbate (DHA), activates induced systemic resistance in rice against the root‐knot nematode Meloidogyne graminicola, and investigate the molecular and biochemical mechanisms underlying this phenotype. Detailed transcriptome analysis on roots of rice plants showed an early and robust transcriptional response on foliar DHA treatment, with induction of several genes related to plant stress responses, immunity, antioxidant activity, and secondary metabolism already at 1 day after treatment. Quantitative and qualitative evaluation of H2O2 levels confirmed the appearance of a reactive oxygen species (ROS) burst on DHA treatment, both at the site of treatment and systemically. Experiments using chemical ROS inhibitors or scavengers confirmed that H2O2 accumulation contributes to DHA‐based induced resistance. Furthermore, hormone measurements in DHA‐treated plants showed a significant systemic accumulation of the defence hormone salicylic acid (SA). The role of the SA pathway in DHA‐based induced resistance was confirmed by nematode infection experiments using an SA‐signalling deficient WRKY45‐RNAi line and reverse transcription‐quantitative PCR on SA marker genes. Our results collectively reveal that DHA activates induced systemic resistance in rice against the root‐knot nematode M. graminicola, mediated through the production of ROS and activation of the SA pathway.


| INTRODUC TI ON
Rice provides the staple food for more than half of the world's population (Beighley, 2010;FAO, 2021). The root-knot nematode (RKN) Meloidogyne graminicola is one of the most important plant-parasitic nematodes affecting rice production (Mantelin et al., 2017;Prasad et al., 2010;Ravindra et al., 2017) and is present in most rice-growing areas globally (Dutta et al., 2012;Mantelin et al., 2017). The threat posed by M. graminicola is growing as traditional flooded rice systems are increasingly replaced by aerobic rice systems that are more water-efficient and ecofriendly but also more amenable to RKN infestation (Mantelin et al., 2017;Ravindra et al., 2017). The second-stage juveniles of M. graminicola can survive and remain viable in soil without a host plant for up to 5 months (Soomro, 1989). The control of RKNs using conventional methods is challenging because of its broad host range, ability to survive in soil, and the lack of a strong resistance source in elite rice cultivars (Bridge et al., 2005;Mantelin et al., 2017;Prasad et al., 2010). Induced resistance (IR) is one of the promising approaches in the search for environmentally-friendly crop protection methods (Martínez-Medina et al., 2017;Van Aubel et al., 2014;Walters & Fountaine, 2009). IR refers to a state of reduced disease susceptibility of a plant induced by exposure to an external stimulus (De Kesel et al., 2021).

Examples of IR stimulants include beneficial microbes such as
Trichoderma spp. (Martínez-Medina et al., 2017), natural compounds like piperonylic acid (Desmedt et al., 2021) and thiamine (Huang et al., 2016), and chemical compounds like the salicylate homologue acibenzolar-S-methyl (Romero et al., 2001). IR involves both the activation of direct defence responses, where defence pathways are induced, locally or systemically, on contact with the IR stimulus (De Kesel et al., 2021), and the so-called (defence) priming phenomenon, where defence responses are more potently activated on subsequent challenge by stress (Conrath et al., 2006). Treatment of plants with IR stimulants leads to local and systemic transcriptional reprogramming and physiological changes (Desmedt et al., 2021;Mauch-Mani et al., 2017). A variety of cellular responses have been reported to contribute to the IR phenotype, including alterations in ion transport across the plasma membrane, synthesis and secretion of secondary metabolites, accumulation of cell wall-bound phenolics and lignin-like polymers, callose deposition, activation of pathogenesis-related (PR) genes, and reactive oxygen species (ROS) signalling (Conrath, 2009).
The oxidative burst-rapid accumulation of ROS, including superoxide radicals, hydrogen peroxide (H 2 O 2 ), and hydroxyl radicals-is a primary feature of plant stress responses (Sharma et al., 2012;Wojtaszek, 1997). ROS are toxic to many organisms, but also act as signals in the induction of defence genes (Kuźniak & Urbanek, 2000).
To be used as signalling molecules, ROS must be maintained at nontoxic levels through delicate balancing between generating and scavenging pathways (Deng et al., 2016). The antioxidant system that regulates H 2 O 2 levels consists of enzymatic and nonenzymatic H 2 O 2 scavengers (Niu & Liao, 2016). Catalase (CAT), superoxide dismutase (SOD), and peroxidases (POX) are among the enzymatic antioxidants that regulate ROS metabolism (Gill & Tuteja, 2010). Nonenzymatic components include ascorbic acid (AsA), tocopherol, flavonoids, glutathione, carotenoids, lipids, and phenolic compounds, which mitigate oxidative damage by scavenging free radicals or by working together with the enzymatic players to achieve antioxidant activity via the utilization of H 2 O 2 (Nadarajah, 2020). Elevated H 2 O 2 levels are associated with resistance of transgenic potato to Erwinia carotovora and Phytophthora infestans (Kuźniak & Urbanek, 2000), thiamine IR in rice against M. graminicola (Huang et al., 2016), ozonated water IR in tomato against Meloidogyne incognita (Veronico et al., 2017), and piperonylic acid IR against pest and diseases in tomato (Desmedt et al., 2021).
Next to ROS and antioxidant signalling, phytohormones are another group of regulators of plant responses to biotic and abiotic stresses (Denancé et al., 2013). Salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) form the central backbone of plant immunity (De Vleesschauwer et al., 2013Spoel & Dong, 2008). SA regulates various aspects of plant growth and development in addition to its role as activator of defence genes (Klessig et al., 2018).
Establishment of systemic acquired resistance (SAR)-a specific type of IR triggered by necrotizing pathogens that leads to resistance in systemic tissues (De Kesel et al., 2021)-involves the generation and transport of signals via the phloem to distal tissues (Guedes et al., 1980), among which SA is a central component of SAR (Gao et al., 2015). IR activated by plant growth-promoting rhizobacteria, necrotizing pathogens, and several chemical compounds, including β-aminobutyric acid, ascorbate oxidase, and piperonylic acid, involves SA accumulation in treated plants (Desmedt et al., 2021;Jakab et al., 2001;Klessig et al., 2018;Singh et al., 2020b).
The antioxidant AsA regulates various plant physiological processes . AsA reacts with ROS generated during stress to form monodehydroascorbate (MDHA), which then dissociates to dehydroascorbate (DHA). MDHA and DHA again get reduced to AsA by monodehydroascorbate reductase and DHA reductase, respectively. This AsA-DHA cycle is highly important for plant growth and development (Suekawa et al., 2018), as well as (a)biotic stress tolerance (Boubakri, 2018;Veljović-Jovanović et al., 2018).
DHA performs unique functions like cell cycle progression sensing and regulation, and modulation of metal stress responses, and DHA adducts seem to be involved in oxidative stress-mediated cellular toxicity (Miret & Müller, 2018;Potters et al., 2000). The changes in the pool and ratio of the AsA/DHA redox pair by both growth and environmental cues modulate gene expression and protein levels, resulting in increased stress tolerance (Miret & Müller, 2018).
Previously, we showed that oxidation of AsA by exogenous application of ascorbate oxidase activates systemic defence mechanisms against plant-parasitic nematodes in rice and sugar beet (Singh et al., 2020b(Singh et al., , 2020a. This led to the hypothesis that the oxidized product of AsA, that is, DHA, might stimulate IR in plants. In the current research paper, we have confirmed this hypothesis and investigated the mechanisms of DHA-based induced resistance in rice against root-knot nematode M. graminicola in detail by performing infection assays, transcriptional analyses, biochemical assays, and hormone measurements.

| DHA reduces plant susceptibility in rice against M. graminicola
In an experiment for the evaluation of different concentrations of DHA, we observed that foliar application of 5-30 mM DHA was effective in reducing susceptibility of rice roots to M. graminicola, with 20 mM being most effective (Figure 1a,b). The number of second-stage juveniles (J2) was significantly lower in DHA-treated plants versus mock-treated control plants at 3 days postinoculation (DPI), indicating that nematode penetration is hampered (Figure 1c).
Furthermore, numbers of galls, nematodes, and egg-laying females were significantly lower in DHA-treated plants versus mock-treated control plants at 2 weeks postinoculation, revealing that nematode development is also affected (Figure 1d,e). These data confirm and extend the previous observations reported in Singh et al. (2020a). F I G U R E 1 Effect of foliar dehydroascorbate (DHA) treatment on rice susceptibility to Meloidogyne graminicola. Two-week-old rice plants were treated with DHA followed by nematode inoculation (250/plant) 1 day posttreatment (DPT). (a) Effect of 1, 5, 10, 20, or 30 mM DHA on plant susceptibility to M. graminicola recorded 14 days after nematode inoculation (14 DPI). Effect of 20 mM DHA on (b) galls and (c) nematodes recorded 3 DPI. Effect of 20 mM DHA on (d) galls and (e) nematodes recorded 14 DPI. Bars represent the means and standard error of eight replicates. The whole experiment was independently repeated three times, providing confirmatory results. Different letters on error bars within a group indicate a statistically significant difference (Duncan's multiple range test, α = 0.05). Asterisks on error bars indicate statistically significant differences with the mock-treated control plants (Student's t test, *p < 0.05, **p < 0.01).
Foliar treatment with DHA did not cause negative effects on rice growth up to a concentration of 30 mM ( Figure S1). To confirm this observation and investigate potential long-term effects, a greenhouse experiment with biweekly 20 mM DHA treatments was executed on two rice cultivars, but again no negative effects were observed ( Figure S2). However, a slight positive effect on plant growth and yield was observed in DHA-treated plants ( Figure S2).

| DHA acts as stimulant of systemic induced resistance in rice
To explore underlying molecular mechanisms of DHA-induced sys-  (Table S3a), while many stress/ defence-related GO terms were additionally enriched on treatment with the 20 mM DHA concentration (Table S3c) (Table S5). Together, these data indicate that DHA induces transcriptional changes consistent with induced systemic resistance in rice. stimuli. This might be because nematode infection has been shown to cause DHA accumulation (Singh et al., 2020a). These shared DEGs were enriched in GO terms associated with, for example, abscisic acid (ABA) binding, hormone binding, chitinase activity, oxidoreductase activity, defence response, and response to stress (Tables S2 and S3).
Importantly, the nematodes, which are well known to interfere with plant metabolism and defence (Ji et al., 2013;Kyndt et al., 2012a), seemed less able to do so when plants were pretreated with DHA (Figures S3 and S4, and Tables S2 and S5 To confirm the role of ROS accumulation in DHA-IR, an infection experiment was conducted on plants treated with ROS inhibitors alone and in combination with DHA. Previous reports showed that plant treatment with DPIC leads to reduced ROS production (Li & Trush, 1998)      These results indicate that DHA-IR is dependent on SA signalling through WRKY45.

| DISCUSS ION
AsA is one of the most abundant water-soluble antioxidants in plants and acts as a key regulator in growth and development , and abiotic (Billah et al., 2017;Farooq et al., 2013;Kobayakawa & Imai, 2017;Wang et al., 2017;Xu & Huang, 2018) as well as biotic stress tolerance (Boubakri, 2018;Egan et al., 2007;Fujiwara et al., 2013;Li et al., 2016). Oxidation of AsA is an impor- A significant reduction in nematode penetration was observed in roots of DHA-treated rice plants (Figure 1c). This is indicative of prepenetration resistance, a situation in which nematodes are unable to enter the host plant due to, for example, absence of the metabolites needed for host recognition, repellent host exudates, or a physical barrier (Desmedt et al., 2020;Lee et al., 2017). Nematodes that fail to establish feeding sites either die or leave the hostile roots, as observed in β-aminobutyric acid-treated rice plants (Ji et al., 2015), and in RKN-resistant cultivars in soybean (Herman et al., 1991) and alfalfa (Griffin & Elgin, 1977;Reynolds et al., 1970). In addition to to ET and JA accumulation in rice roots (Singh et al., 2020a), and SA accumulation in sugar beet (Singh et al., 2020b). Contrary to reports on SA-JA antagonism in Arabidopsis defence against aboveground pathogens (Pieterse et al., 2009), these hormones rather seem to collaborate in root defence against RKNs (Martínez-Medina et al., 2017;Nahar et al., 2011). Here, activation of the JA pathway was only observed in the mRNA-Seq dataset ( Figure S3 and Table S5b), while lower endogenous levels were observed at 4 DPT ( Figure 4d). These data are indicative of a negative feedback loop and suggest that the JA peak was probably already occurring before 1 DPT.
The defence responses underlying IR can be activated directly and/or be primed for augmented expression on stress exposure (De Kesel et al., 2021;Van Hulten et al., 2006). The IR-stimulating chemical compound diproline leads to a direct activation of defence genes in rice (De Kesel et al., 2020), while AO (Singh et al., 2020a) and piperonylic acid (Desmedt et al., 2021) activate both direct and primed defence responses in rice and tomato, respectively. In our study, we observed a strong transcriptional response, as well as While both AsA and DHA are well-known antioxidants (Dewhirst & Fry, 2018), the pro-oxidant nature of both compounds has also been described (Kärkönen & Fry, 2006;Smirnoff, 2018). DHA degradation in planta can produce a range of products that give rise to H 2 O 2 (Deutsch, 2000;Parsons et al., 2011;Smirnoff, 2018), which could influence defence responses and cell wall polymer cross-linking processes that depend on H 2 O 2 and peroxidases (Smirnoff, 2018).
Stimulation of APX and GPOX on DHA treatment confirms the activation of ROS metabolism in DHA-treated plants (Figure 3c,d). Such increased peroxidase activity has also been reported during the activation of IR by plant growth-promoting rhizobacteria and chemical compounds (Anand et al., 2007;Naz et al., 2021;Retig, 1974;Survila et al., 2016;Yanti, 2015). shoots but not in roots (Singh et al., 2020a), indicating that a compound other than DHA is transported to the roots. Accumulation of H 2 O 2 and SA in roots of DHA-treated plants (Figures 3a,b and 4b) suggests they might play a role in systemic DHA-IR, as systemic signalling by SA (Ament et al., 2010;Dempsey & Klessig, 2012;Koo et al., 2007;Rowen et al., 2017;Shulaev et al., 1997) Rao et al., 1997), and conversely SA accumulation can be induced by increased H 2 O 2 levels (Chamnongpol et al., 1998). ROS signals are thus involved both upstream and downstream of SA signalling (Herrera-Vásquez et al., 2015). Typically, H 2 O 2 is an early signalling molecule in plant stress responses (Černý et al., 2018). In light of our understanding of the ROS burst as a trigger for SA signalling (Chaouch et al., 2010;Herrera-Vásquez et al., 2015;Mammarella et al., 2015;Maruta et al., 2012;Noshi et al., 2012;Wrzaczek et al., 2013), we hypothesize that DHA treatment in rice causes increased accumulation of ROS, after which ROS activates SA signalling by a primed induction of WRKY45. This then leads to reduced rice susceptibility to M. graminicola.

| Plant material and growth conditions
Seeds of rice Oryza sativa 'Nipponbare' (GSOR-100; USDA) and the SA signalling deficient WRKY45-RNAi line (Shimono et al., 2007) were germinated in the dark for 4 days at 30°C. The WRKY45-RNAi line was confirmed to have a significantly lower expression of WRKY45 compared to wild-type Nipponbare ( Figure S6). Sprouted seeds were transferred to polyvinyl chloride (PVC) tubes (diameter 3 cm, length 18 cm) containing SAP substrate (sand mixed with Absorbent Polymer AquaPerla; DCM) (Reversat et al., 1999). They were further grown in a rice growth room at 26°C under 12 h/12 h light/dark regime (150 μmol·m −2 ·s −1 ) and relative humidity of 70%-75%. Plants were watered three times a week with 10 ml of Hoagland's solution (Hoagland & Arnon, 1950).

| Nematode culture, inoculation, and evaluation of plant susceptibility
A pure culture of M. graminicola was originally obtained from the Philippines (kindly provided by Professor Dirk De Waele, KU Leuven) and maintained on barnyard grass (Echinochloa crus-galli). Secondstage juveniles (J2) were extracted from infected plants following a modified Baermann funnel method (Whitehead & Hemming, 1965).
Two-week-old plants were inoculated with 250 J2s or mockinoculated with water at 1 DPT. Plant susceptibility was assessed at 3 DPI by counting number of J2s penetrated in roots and at 2 weeks after nematode inoculation by counting galls, total nematodes, and egg-laying females using the acid fuchsin staining technique (Byrd et al., 1983). Galls and nematodes were counted using a binocular stereomicroscope (SMZ1500; Nikon). All infection experiments were repeated at least twice, each time using 8-12 plants per treatment.

| Chemical treatments
The concentration of DHA (l-dehydroascorbic acid; Sigma-Aldrich) was optimized for efficacy against M. graminicola and lack of phytotoxicity by evaluating 1, 5, 10, 20, or 30 mM DHA. The aboveground parts of each plant were sprayed until run-off with a 6.25 ml of DHA solution or distilled water, both containing 0.02% (vol/vol) of Tween 20 (Sigma-Aldrich) for efficient spread and uptake of chemicals (Nahar et al., 2011). Plants were inoculated with nematodes 1 DPT. Among these concentrations, a range of 5-30 mM DHA was effective in reducing rice susceptibility without negatively affecting plant growth (Figures 1a and S1). No supplementary reduction in plant susceptibility was observed beyond the 20 mM concentration.
One low (5 mM) and one high (20 mM) effective DHA concentration was used for mRNA-Seq analysis. A concentration of 20 mM DHA was used for all further experiments.
To evaluate potential long-term effects on rice growth and yield, a greenhouse experiment was conducted using two different rice cultivars (Kitaake and Nipponbare Bio-Rad). The denatured library was diluted to a final concentration of 6 pM and loaded into a flow cell (Illumina). After cluster generation, the multiplexed library was sequenced on an Illumina NextSeq 500 System (75 cycles, single-end, high output).
Reads were trimmed with Trimmomatic v. 0.36 (Bolger et al., 2014) and mapped against the Oryza sativa subsp. japonica 'Nipponbare' reference genome (build MSU7.0) using STAR v. 2.5.2a (Dobin et al., 2013). Only uniquely mapped reads were used for further analysis. BAM files of multiplexed samples were merged using samtools v. 1.3. Count tables were generated by the 'Summarize Overlaps' function in the Genomic Alignments R package v. 1.16.0 (Lawrence et al., 2013). The baseline characteristics of RNA-Seq data are provided in Table S6. Differential gene expression analysis was performed using DESeq2 v. 1.20 (Love et al., 2014) with the annotations from the Rice Annotation Project Database v. 38. Genes with a false discovery rate (FDR) <0.05 were considered differentially expressed compared to the control group. The complete list of differentially expressed genes for all comparisons is provided in Table S7.
Gene Ontology (GO) enrichment analysis on DEGs was performed using g:Profiler v. e102_eg49_p15_7a9b4d6 with g:SCS multiple testing correction and a significance threshold of 0.05 (Raudvere et al., 2019). MapMan (Thimm et al., 2004) was used to visualize expression of genes involved in various metabolic pathways.
The WSR test (with Benjamini-Hochberg correction) was used to test the statistical significance of differential expression of these pathways. The unprocessed mRNA-Seq data can be retrieved from NCBI as BioProject PRJNA767540.

| Biochemical assays
In each biochemical assay described below, root samples were col-

| APX activity
APX activity was measured by monitoring the decrease in absorbance at 290 nm as described by Nakano and Asada (1981)  replicates. One unit of peroxidase was expressed as the amount of enzyme that causes the formation of 1 mM of tetraguaiacol per minute (Uarrota et al., 2016). We analysed six biological replicates, each containing the pooled material of at least four plants.

| Plant hormone measurements
Levels of IAA, SA, ABA, and JA were measured in root material using a UHPLC Q-Exactive high-resolution Orbitrap mass spectrometer (Thermo Fisher Scientific) following a cold solvent (modified Bieleski) extraction and centrifugal filtration clean-up, according to the protocol described in Haeck et al. (2018). ET measurement was performed using gas chromatography (Thermo Finnigan TRACE GC Ultra) according to the procedure described by Singh et al. (2020a).
We analysed six biological replicates per treatment, each containing the pooled material of at least four plants.

| RT-qPCR
RNA was extracted from root tissues using the RNeasy Plant Mini Kit (Qiagen) and treated with DNase I (ThermoFisher Scientific).
First-strand cDNA was synthesized using a Tetro cDNA Synthesis Kit (Bioline). All qPCRs were performed using a SensiMix SYBR HI-ROX kit (Bioline) on three biological and three technical replicates with a CFX Connect Real-Time PCR Detection System (Bio-Rad), using the conditions as described in De Kesel et al. (2020). Primers are listed in Table S1. Gene expression levels were normalized using two reference genes (Kyndt et al., 2012b) and the data were statistically analysed using REST 2009 (Pfaffl et al., 2002). The assumptions of normality and homogeneity of the data were checked and found to be fulfilled.

ACK N OWLED G EM ENTS
This work was supported by a Netaji Subhash Indian Council of Agricultural Research (ICAR) international fellowship awarded to S.N.C., which was funded by the Government of India. We also want to thank Lien De Smet and Patrick De Wispelaere for their excellent technical support. The EnVOC research group is part of the Ghent University expertise centre MSsmall. The authors also acknowledge financial support (AUGE/11/016) from the Hercules Foundation of the Flemish Government for the UHPLC-Q-Exactive mass spectrometry equipment.

CO N FLI C T O F I NTE R E S T
The authors declare that they have no conflict of interests.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are openly available at NCBI https://www.ncbi.nlm.nih.gov/biopr oject, as BioProject PRJNA767540.

S U PP O RTI N G I N FO R M ATI O N
Additional supporting information may be found in the online version of the article at the publisher's website.